The effects of visual apparency on bias in butterfly recording and monitoring

By R. Dennis, T. Shreeve, Nick J B Isaac, David Roy, P. Hardy, R. Fox, J. Asher. 2006

107 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Evolution, Behavior and Systematics, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/14273dccfff69c075e166c1e20be80e9e4b6d4f4

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In Ecological Modeling

In Ecology, Evolution, Behavior and Systematics

In Nature and Landscape Conservation

Citations in the corpus

Species richness estimation and determinants of species detectability in butterfly monitoring programmes (2007, methodology): “Few such studies on such issues are available for invertebrate taxa ( McCoy, 1999; King & Porter, 2005; Dorazio et al. , 2006 ).”
Exploring the effects of quantity and location of pseudo-absences and sampling biases on the performance of distribution models with limited point occurrence data (2011, background): “(Dennis & Hardy 1999; Dennis et al. 1999; Dennis & Thomas 2000; Dennis et al. 2006; Zaniewski et al. 2002; Anderson 2003; Reutter et al. 2003; Graham et al. 2004; Soberón & Peterson 2004; Martínez-Meyer 2005).”
The generalist―specialist continuum: Testing predictions for distribution and trends in British butterflies (2013, unknown): “Although care is taken to ensure that data are collected using standardized effort, distribution and population trend data are potentially influenced by conspicuousness of species to observers (Dennis et al., 2006; Isaac et al., 2011) and there is both turnover of recorders (naive recorders joining)”
The use of opportunistic data for IUCN Red List assessments (2015, background): “…not all areas are surveyed with an equal intensity – Dennis, Sparks & Hardy, 1999), but also in volunteer preferences for taxonomic groups (e.g., birds, mammals, butterflies) and in differences in observation volunteer skills (e.g., identification errors, detectability - Dennis et al., 2006).”
Statistics for citizen science: extracting signals of change from noisy ecological data (2014, unknown): “This species-specific detection probability can be thought of as the product of visual apparency (Dennis et al. 2006) and mean abundance.”
Butterfly monitoring in Europe: methods, applications and perspectives (2008, background): “Observers never detect all butterfly individuals present during their visit in the study area (Dennis et al. 2006; Kéry and Plattner 2007).”
Distance sampling and the challenge of monitoring butterfly populations (2011, unknown): “Species traits were wingspan (in mm), bask mode (dorsal vs lateral) and colour measured from 1 (dull) to 5 (very bright), all using data presented in Dennis et al. (2006).”
The dragonfly delusion: why it is essential to sample exuviae to avoid biased surveys (2010, methodology): “2004), they generally suffer from coverage and recorder bias (Dennis and Shreeve 2003; Maes et al. 2003; Dennis et al. 2006).”
Monitoring insect pollinators and flower visitation: The effectiveness and feasibility of different survey methods (2019, background): “Transects and timed focal floral observations are straightforward to conduct and can generate data on insect-plant interactions but depend on the expertise of the observer (Sutherland, Roy, & Amano, 2015) and may be biased towards more conspicuous species (Dennis et al., 2006).”